50 research outputs found

    Spatial Relation of Apparent Soil Electrical Conductivity with Crop Yields and Soil Properties at Different Topographic Positions in a Small Agricultural Watershed

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    Use of electromagnetic induction (EMI) sensors along with geospatial modeling provide a better opportunity for understanding spatial distribution of soil properties and crop yields on a landscape level and to map site-specific management zones. The first objective of this research was to evaluate the relationship of crop yields, soil properties and apparent electrical conductivity (ECa) at different topographic positions (shoulder, backslope, and deposition slope). The second objective was to examine whether the correlation of ECa with soil properties and crop yields on a watershed scale can be improved by considering topography in modeling ECa and soil properties compared to a whole field scale with no topographic separation. This study was conducted in two headwater agricultural watersheds in southern Illinois, USA. The experimental design consisted of three basins per watershed and each basin was divided into three topographic positions (shoulder, backslope and deposition) using the Slope Position Classification model in ESRI ArcMap. A combine harvester equipped with a GPS-based recording system was used for yield monitoring and mapping from 2012 to 2015. Soil samples were taken at depths from 0–15 cm and 15–30 cm from 54 locations in the two watersheds in fall 2015 and analyzed for physical and chemical properties. The ECa was measured using EMI device, EM38-MK2, which provides four dipole readings ECa-H-0.5, ECa-H-1, ECa-V-0.5, and ECa-V-1. Soybean and corn yields at depositional position were 38% and 62% lower than the shoulder position in 2014 and 2015, respectively. Soil pH, total carbon (TC), total nitrogen (TN), Mehlich-3 Phosphorus (P), Bray-1 P and ECa at depositional positions were significantly higher compared to shoulder positions. Corn and soybeans yields were weakly to moderately

    Quantifying the Water Quality Benefits of Riparian Buffers in the Cache River Watershed

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    In agricultural watersheds across the U.S. and world, many woody and herbaceous species of riparian vegetation have proven to be effective filters of nutrients and sediment. Over the past decade, we have investigated the water quality impacts of giant cane (Arundinaria gigantea (Walt.) Muhl.) riparian buffers in the Cache River watershed. Giant cane is a native bamboo-like grass species that once thrived in southern Illinois and has received considerable attention from federal and state agencies for reestablishment into its native range. A series of three field-scale studies evaluated giant cane’s ability to attenuate sediment and nutrients in surface runoff and groundwater. The initial study monitored nutrient and sediment concentrations in surface runoff and groundwater in Cypress Creek watershed, while two subsequent studies focused on groundwater quality and added riparian buffer plots along Big Creek and Cache River. Overland flow collectors and groundwater monitoring wells were used to collect water samples at fixed distances from the edge of three agricultural fields (i.e., 0m, 1.5m, 3m, 6m, 9m, and 12m). Results showed significant nutrient and sediment reductions within the first 3m of the giant cane buffers, whereas equivalent reductions were observed at ~6m in adjacent forested buffers. Nutrient reductions in overland flow in the cane buffer were 80%, 80%, and 68% for phosphate, dissolved ammonium, and dissolved nitrate, respectively. Further, sediment (97%) and groundwater nitrate concentrations (90%) were significantly reduced in the initial 3m of the cane buffers. Microbial denitrification was likely the most important groundwater nitrate loss mechanism, given the relatively deep ground water depths (\u3e 2 m) at the study sites. High stem density and infiltration rates promoted deposition of sediment and sediment-bound nutrients in the first 1.5 to 3 meters of the buffers. Currently, a paired watershed experiment is being conducted on SIUC farms properties to quantify the water quality benefits of giant cane and deciduous forest buffers in row-crop agricultural watersheds with no artificial drainage. Further, a giant cane nursery has been established to help provide propagules for future restoration efforts

    Comparison of Terrain Indices and Landform Classification Procedures in Low-Relief Agricultural Fields

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    Landforms control the spatial distribution of numerous factors associated with agronomy and water quality. Although curvature and slope are the fundamental surface derivatives used in landform classification procedures, methodologies for landform classifications have been performed with other terrain indices including the topographic position index (TPI) and the convergence index (CI). The objectives of this study are to compare plan curvature, the convergence index, profile curvature, and the topographic position index at various scales to determine which better identifies the spatial variability of soil phosphorus (P) within three low relief agricultural fields in central Illinois and to compare how two methods of landform classification, e.g. Pennock et al. (1987) and a modified approach to the TPI method (Weiss 2001, Jenness 2006), capture the variability of spatial soil P within an agricultural field. Soil sampling was performed on a 0.4 ha grid within three agricultural fields located near Decatur, IL and samples were analyzed for Mehlich-3 phosphorus. A 10-m DEM of the three fields was also generated from a survey performed with a real time kinematic global positioning system. The DEM was used to generate rasters of profile curvature, plan curvature, topographic position index, and convergence index in each of the three fields at scales ranging from 10 m to 150 m radii. In two of the three study sites, the TPI (r ≥ -0.42) was better correlated to soil P than profile curvature (r ≤ 0.41), while the CI (r ≥ -0.52) was better correlated to soil P than plan curvature (r ≥ -0.45) in all three sites. Although the Pennock method of landform classification failed to identify footslopes and shoulders, which are clearly part of these fields’ topographic framework, the Pennock method (R² = 0.29) and TPI method (R² = 0.30) classified landforms that captured similar amounts of soil P spatial variability in two of the three study sites. The TPI and CI should be further explored when performing terrain analysis at the agricultural field scale to create solutions for precision management objectives

    Resonance Raman studies of Rieske-type proteins

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    Resonance Raman (RR) spectra are reported for the [2Fe-2S] Rieske protein from Thermus thermophilus (TRP) and phthalate dioxygenase from Pseudomonas cepacia (PDO) as a function of pH and excitation wavelength. Depolarization ratio measurements are presented for the RR spectra of spinach ferredoxin (SFD), TRP, and PDO at 74 K. By comparison with previously published RR spectra of SFD, we suggest reasonable assignments for the spectra of TRP and PDO. The spectra of PDO exhibit virtually no pH dependence, while significant changes are observed in TRP spectra upon raising the pH from 7.3 to 10.1. One band near 270 cm-1, which consists of components at 266 cm-1 and 274 cm-1, is attributed to Fe(III)-N(His) stretching motions. We suggest that these two components arise from conformers having a protonated-hydrogen-bonded imidazole (266 cm-1) and deprotonated-hydrogen-bonded imidazolate (274 cm-1) coordinated to the Fe/S cluster and that the relative populations of the two species are pH-dependent; a simple structural model is proposed to account for this behavior in the respiratory-type Rieske proteins. In addition, we have identified RR peaks associated with the bridging and terminal sulfur atoms of the Fe-S-N cluster. The RR excitation profiles of peaks associated with these atoms are indistinguishable from each other in TRP (pH 7.3) and PDO and differ greatly from those of [2Fe-2S] ferredoxins. The profiles are bimodal with maxima near 490 nm and > approx. 550 nm. By contrast, bands associated with the Fe-N stretch show a somewhat different enhancement profile. Upon reduction, RR peaks assigned to Fe-N vibrations are no longer observed, with the resulting spectrum being remarkably similar to that reported for reduced adrenodoxin. This indicates that only modes associated with Fe-S bonds are observed and supports the idea that the reducing electron resides on the iron atom coordinated to the two histidine residues. Taken as a whole, the data are consistent with an St2FeSb2Fe[N(His)]t2 structure for the Rieske-type cluster.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29687/1/0000014.pd

    Cover Crops for Managing Stream Water Quantity and Improving Stream Water Quality of Non-Tile Drained Paired Watersheds

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    In the Midwestern United States, cover crops are being promoted as a best management practice for managing nutrient and sediment losses from agricultural fields through surface and subsurface water movement. To date, the water quality benefits of cover crops have been inferred primarily from plot scale studies. This project is one of the first to analyze the impacts of cover crops on stream water quality at the watershed scale. The objective of this research was to evaluate nitrogen, phosphorus, and sediment loss in stream water from a no-till corn-soybean rotation planted with winter cover crops cereal rye (Secale cereale) and hairy vetch (Vicia villosa) in non-tile drained paired watersheds in Illinois, USA. The paired watersheds are under mixed land use (agriculture, forest, and pasture). The control watershed had 27 ha of row-crop agriculture, and the treatment watershed had 42 ha of row crop agriculture with cover crop treatment (CC-treatment). During a 4-year calibration period, 42 storm events were collected and Event Mean Concentrations (EMCs) for each storm event were calculated for total suspended solids (TSS), nitrate-N (NO3-N), ammonia-N (NH4-N), dissolved reactive phosphorus (DRP), and total discharge. Predictive regression equations developed from the calibration period were used for calculating TSS, NO3-N, NH4-N, and DRP losses of surface runoff for the CC-treatment watershed. The treatment period consisted of total 18 storm events, seven of which were collected during the cereal rye, eight in the hairy vetch cover crop season and three during cash crop season. Cover crops reduced TSS and discharge by 33% and 34%, respectively in the CC-treatment watershed during the treatment period. However, surprisingly, EMCs for NO3-N, NH4-N, and DRP did not decrease. Stream discharge from the paired-watersheds will continue to be monitored to determine if the current water quality results hold or new patterns emerge

    Monitoring of Water and Solute Transport in the Vadose Zone: A Review

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    A number of contaminants including agrochemicals (fertilizers, pesticides), heavy metals, trace elements, and pathogenic microbes along with pharmaceuticals and hormones used in animal production move through the soil and are responsible for degradation of groundwater quality. Therefore, it is essential to sample soil solution for better understanding of movement and environmental fate of various contaminants in soils. We review different soil solution extraction samplers. The soil solution samplers discussed here are: drainage lysimeter or soil column, pan lysimeter, resin bags or membranes, wick lysimeters, suction cup, and suction plate. We have reviewed 304 journal articles representing a wide array of scientific disciplines. A brief history of soil solution monitoring and terminology used for describing various soil solution samplers is also provided. This review classifies literature on the basis of type of soil solution extraction samplers, soil type, land use–land cover (LULC), and analytes measured. Recommendation criteria are provided for selecting appropriate soil solution extraction samplers based on spatial and temporal variation, cost, soil type, amount of disturbance caused during installation of soil solution samplers, and monitoring of leachates involving different cations, anions, carbon, pH, EC, colloids, pesticides, and microbes. Use of advanced techniques with lysimeters for monitoring soil moisture content, soil water potential and flux is also discussed in this review
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